Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/optimeta/paideia/mockgit clone --depth 1 https://github.com/OPTIMETA/PAIDEIAWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00037 | $0.00681 |
| Opus 5 | $0.00018 | $0.00341 |
| Sonnet 5 | $0.00007 | $0.00136 |
| Haiku 4.5 | $0.00004 | $0.00068 |
Grade A, and why
mock scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Output language
Read INTERFACE_LANG from .course-meta (default en). All user-facing prose must be in that language. Keep in English regardless: file paths, slash command names, pattern IDs, LaTeX, tier markers, and the mock exam's structural labels (# Mock Exam — <date>, **Duration**, **Total**, ## P<n>).
Load skills/exam-drill/SKILL.md. Read course-index/summary.md, course-index/patterns.md, course-index/coverage.md.
Arguments: $ARGUMENTS
(First token: minutes. Remaining: optional emphasize=... list.)
Procedure:
-
Infer exam structure from
coverage.mdand past HW:- Typical mid/final: 4–6 problems, 2 hours
- HW-weighted mix. Problems are drawn in proportion to HW density of each section. Rough target:
- ≥70% of points from 🔥🔥 Exam-primary sections (3+ HW)
- ~25% from 🔥 Exam-likely (2 HW)
- ≤5% from 🟡 Exam-possible (1 HW)
- 0% from ⚪ Low-risk (no HW) — do not invent problems in sections the professor never tested.
- If user passed
emphasize=§X,§Y, bias toward those (override the HW weighting if they override explicitly). - Difficulty distribution: 1 warmup / N-2 standard / 1 hard (multi-pattern)
-
Design the exam:
- For each problem, pick: target §, target pattern(s), point value, estimated time
- Ensure patterns from ≥3 different parts of the course appear (tests integration)
- Last problem should require chaining ≥2 patterns
-
Save:
- Problems →
mock/exam_<ts>.md - Solutions →
mock/exam_<ts>_sol.md(do not display)
- Problems →
-
Print to chat:
- The full exam (problem statements with point values and time suggestions)
- Total points summing to 100 (or inferred weighting)
- Closing line (in $INTERFACE_LANG): "Timer: $ARGUMENTS min. Solve on paper, upload as
answers/mock_<ts>.pdf, then/grade."
-
Do NOT reveal which patterns are being tested in the problem statements. The user should identify them during solving.
Exam format
# Mock Exam — <date>
**Duration**: <minutes> min **Total**: 100 pts
---
## P1 (<pts>, ~<min> min)
<problem>
## P2 (<pts>, ~<min> min)
<problem>
...
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 64 lines · 37 tokens per session scan A 2aa82edae8db
mock is a command published in the GitHub repository OPTIMETA/PAIDEIA (91 stars, last pushed 1mo ago), licensed MIT. It adds 37 tokens to every session and 681 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
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book-characters
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learn
Append a lesson to an agent's learnings journal (.claude/learnings/ .md).
recall
Search past session observations and lessons for relevant context. Wrap the memorysmartsearch and memorylessonrecall MCP tools.
tree
Show file tree with sync status indicators showing which files are indexed, modified, new, or deleted.
repo-overview
Generate a one-paragraph overview of the current repository.